Computerized data processing systems for processing financial transactions have become increasingly more complex as further strides toward automation have occurred. Such complexity has generated a number of related difficulties for the financial data processing industry. In particular, complex financial transaction processing systems may have subtle programming defects or errors that may go unnoticed for long periods of time before the extent of the problems thereby generated are fully recognized. For example, the number of positions allotted for the dating of transactions has recently been problematic, wherein the dates for the millennium starting at the year 2000 can be problematic for many financial transaction processing systems.
In addition, such complex financial transaction processing systems also are typically incapable of being fully audited. That is, it is common practice in the financial data processing industry to provide only partial auditability in that it is generally believed that the amount of data required to be stored for full auditability is so large as to not be cost effective.
Further, in many circumstances, the rate of transaction increase is becoming problematic in that progressively larger computers are required for processing financial transactions at an acceptable rate. This problem is exacerbated by the fact that such transaction processing systems are not architected for use on multi-processing machines having a plurality of processors. Thus, the advantages of parallel-processing computers cannot be fully utilized by such systems.
Accordingly, it would be advantageous to have a financial transaction processing system that alleviates the above difficulties, and that additionally, provides flexibility to adapt to the changing business needs of business enterprises so that the transactions processed and the respective reports generated may be modified easily according to business constraints and demands.